Ijcot v5p302

International Journal of Computer & Organization Trends – Volume 5 – February 2014

Dynamic Data Possession and Review in Cloud Jayashri.T.D*1

V.Udhaya Kumar*2

PG Student Department of Computer Science and Engineering PRIST University Pondicherry, India.

Assistant professor Department of Computer Science and Engineering PRIST University Pondicherry, India.

ABSTRACT Today we have got an inclination to transfer our data through mails and phones. There is a development attained instantly inside the sphere of technology. Computing service has become cheaper and powerful. Here it permits the user to store data and access it remotely at the time of their wishes by inflicting no burden to native hardware and code management. though the access of data is remote it's not secure. The information is changed by others United Nations agency to boot use it. There arises a risk in correctness of the information in cloud. therefore on agitate this new downside and extra come back through a secure and dependable cloud storage service, we have got an inclination to propose throughout this paper a flexible distributed storage integrity auditing mechanism, utilizing the homomorphic token and removal or alter the given data. The planned vogue allows users to check the cloud storage with really light-weight communication and computation value. The checking result not exclusively ensures durable cloud storage correctness guarantee, but to boot at a similar time achieves fast data error localization, i.e., the identification of misbehaving server. Considering the cloud data unit dynamic in nature, the planned vogue further supports secure and economical dynamic operations on outsourced data, along with block modification, deletion, and append.

Analysis shows the planned theme is very economical and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks.

KEYWORDS: Cloud Service Provider (CSP), Third Party Auditor (TPA) ones in this field to consider distributed data storage in Cloud

I. INTRODUCTION In this paper, we propose an effective and flexible distributed scheme with explicit dynamic data support to ensure the correctness of users’ data in the cloud. We rely on

Computing. Our contribution can be summarized as the following three aspects: 

Compared to many of its predecessors, which only

erasure correcting code in the file distribution preparation to

provide binary results about the storage state across the

provide redundancies and guarantee the data dependability.

distributed servers, the challenge-response protocol in our

This construction drastically reduces the communication and

work further provides the localization of data error.

storage overhead as compared to the traditional replicationbased

file

distribution

techniques.

By

utilizing



Unlike most prior works for ensuring remote data

the

integrity, the new scheme supports secure and efficient

homomorphic token with distributed verification of erasure-

dynamic operations on data blocks, including: update,

coded data, our scheme achieves the storage correctness

delete and append.

insurance as well as data error localization: whenever data



Extensive security and performance analysis shows that

corruption has been detected during the storage correctness

the proposed scheme is highly efficient and resilient

verification,

against Byzantine failure, malicious data modification

our

scheme

can

almost

guarantee

the

simultaneous localization of data errors, i.e., the identification

attack, and even server colluding attacks.

of the misbehaving server(s).Our work is among the first few

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International Journal of Computer & Organization Trends – Volume 5 – February 2014 ensure the correctness of users’ data in the cloud, we propose

II. IMPLEMENTATION Implementation is the stage of the project when the theoretical design is turned out into a working system. Thus it can be considered to be the most critical stage in achieving a successful new system and in giving the user, confidence that the new system will work and be effective.

an effective and flexible distributed scheme with two salient features, opposing to its predecessors. By utilizing the homomorphic token with distributed verification of erasurecoded data, our scheme achieves the integration of storage correctness insurance and data error localization, i.e., the identification of misbehaving server(s). Unlike most prior

The implementation stage involves careful planning,

works, the new scheme further supports secure and efficient

investigation of the existing system and it’s constraints on

dynamic operations on data blocks, including: data update,

implementation, designing of methods to achieve changeover

delete and append. In this paper, we propose an effective and

and evaluation of changeover methods.

flexible distributed scheme with explicit dynamic data support to ensure the correctness of users’ data in the cloud.

A. Algorithm: Cloud Computing is not just a third party data

Correctness Verification and Error Localization

warehouse. The data stored in the cloud may be frequently Error

localization

is

a

key

prerequisite

for

updated

by

the

users,

including

insertion,

deletion,

eliminating errors in storage systems. However, many

modification, appending, etc. To ensure storage correctness

previous schemes do not explicitly consider the problem of

under dynamic data update is hence of paramount importance.

data error localization, thus only provide binary results for the

However, this dynamic feature also makes traditional integrity

storage verification. Our scheme outperforms those by

insurance techniques futile and entails new solutions.

integrating the correctness verification and error localization in our challenge-response protocol: the response values from servers for each challenge not only determine the correctness

III. MODULES DESCRIPTION 1. System Model

of the distributed storage, but also contain information to User: users, who have data to be stored in the cloud and rely

locate potential data error(s).

on the cloud for data computation, consist of both individual consumers and organizations.

B .Existing System: In contrast to traditional solutions, where the IT

Cloud Service Provider (CSP): a CSP, who has significant

services are under proper physical, logical and personnel

resources and expertise in building and managing distributed

controls, Cloud Computing moves the application software

cloud storage servers, owns and operates live Cloud

and databases to the large data centers, where the management

Computing systems.

of the data and services may not be fully trustworthy. This unique attribute, however, poses many new security

Third Party Auditor (TPA): an optional TPA, who has

challenges which have not been well understood.

expertise and capabilities that users may not have, is trusted to assess and expose risk of cloud storage services on behalf of

 No user data privacy

the users upon request.

 Security risks towards the correctness of the data in 2. File Retrieval and Error Recovery

cloud.

Since our layout of file matrix is systematic, the user

C. Proposed System:

can reconstruct the original file by downloading the data We focus on cloud data storage security, which has

vectors from the first m servers, assuming that they return the

always been an important aspect of quality of service. To

correct response values. Notice that our verification scheme is

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International Journal of Computer & Organization Trends – Volume 5 – February 2014 based on random spot-checking, so the storage correctness

storage is bulk append, in which the user needs to upload

assurance is a probabilistic one. We can guarantee the

a large number of blocks (not a single block) at one time.

successful file retrieval with high probability. On the other hand, whenever the data corruption is detected, the

CONCLUSION

comparison of pre-computed tokens and received response

In this paper, we investigate the problem of data

values can guarantee the identification of misbehaving

security in cloud data storage, which is essentially a

server(s).

distributed storage system. To achieve the assurances of cloud data integrity and availability and enforce the quality of

3. Third Party Auditing

dependable cloud storage service for users, we propose an

As discussed in our architecture, in case the user

effective and flexible distributed scheme with explicit

does not have the time, feasibility or resources to perform the

dynamic data support, including block update, delete, and

storage correctness verification, he can optionally delegate

append. We rely on erasure-correcting code in the file

this task to an independent third party auditor, making the

distribution preparation to provide redundancy parity vectors

cloud storage publicly verifiable. However, as pointed out by

and guarantee the data dependability. By utilizing the

the recent work, to securely introduce an effective TPA, the

homomorphic token with distributed verification of erasure-

auditing process should bring in no new vulnerabilities

coded data, our scheme achieves the integration of storage

towards user data privacy. Namely, TPA should not learn

correctness insurance and data error localization, i.e.,

user’s data content through the delegated data auditing.

whenever data corruption has been detected during the storage correctness verification across the distributed servers, we can

4. Cloud Operations

almost guarantee the simultaneous identification of the 1) Update Operation In cloud data storage, sometimes the user may need to modify some data block(s) stored in the cloud, we refer this operation as data update. In other words, for all the unused tokens, the user needs to exclude every occurrence of the old data block and replace it with the new one.

misbehaving server(s). Considering the time, computation resources, and even the related online burden of users, we also provide the extension of the proposed main scheme to support third-party auditing, where users can safely delegate the integrity checking tasks to third-party auditors and be worryfree to use the cloud storage services. Through detailed security and extensive experiment results, we show that our

2) Delete Operation Sometimes, after being stored in the cloud, certain data blocks may need to be deleted. The delete operation we are considering is a general one, in which user replaces the data block with zero or some special

scheme is highly efficient and resilient to Byzantine failure, malicious data modification attack, and even server colluding attacks.

REFERENCES

reserved data symbol. From this point of view, the delete operation is actually a special case of the data update operation, where the original data blocks can be replaced

1. C.Wang, Q.Wang, K.Ren, and W.Lou,“Ensuring data storage security incloud computing,” in Proc. of IWQoS ’09, July 2009, pp.

1–9.

with zeros or some predetermined special blocks.

2. M.Arrington, “Gmail disaster: Reports of mass email deletions,”

3) Append Operation In some cases, the user may want to increase the size of his stored data by adding blocks at the end of the data file, which we refer as data append. We anticipate

Online at http:/ /www. techcrunch.com /2006 /12/ 28/gmail-disaster reports-of-mass-email-deletions/, December 2006.

3. Amazon.com, “Amazon Web Services (AWS),” Online at http://aws.amazon.com, 2008.

that the most frequent append operation in cloud data

ISSN: 2249-2593

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International Journal of Computer & Organization Trends – Volume 5 – February 2014 4.G.Ateniese, R. D. Pietro, L. V. Mancini, and G. Tsudik,“Scalable and Efficient Provable Data Possession,” Proc. of Secure Comm ’08, pp. 1–10, 2008.

5.

Google

App

Engine,

Online

at

http://

code

.google.

com/appengine/ 6. MicrosoftAzure http://www.microsoft.com/azure/.

7. A.Agrawal et al. Ws-bpel extension for people (bpel4people), version 1.0., 2007.

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